IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1787-d1065133.html
   My bibliography  Save this article

Hybrid AC/DC Microgrid Energy Management Strategy Based on Two-Step ANN

Author

Listed:
  • Tae-Gyu Kim

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Hoon Lee

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Chang-Gyun An

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Junsin Yi

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Chung-Yuen Won

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

Abstract

In grid-connected operations, a microgrid can solve the problem of surplus power through regeneration; however, in the case of standalone operations, the only method to solve the surplus power problem is charging the energy storage system (ESS). However, because there is a limit to the capacity that can be charged in an ESS, a separate energy management strategy (EMS) is required for stable microgrid operation. This paper proposes an EMS for a hybrid AC/DC microgrid based on an artificial neural network (ANN). The ANN is composed of a two-step process that operates the microgrid by outputting the operation mode and charging and discharging the ESS. The microgrid consists of an interlinking converter to link with the AC distributed system, a photovoltaic converter, a wind turbine converter, and an ESS. The control method of each converter was determined according to the mode selection of the ANN. The proposed ANN-based EMS was verified using a laboratory-scale hybrid AC/DC microgrid. The experimental results reveal that the microgrid operation performed stably through control of individual converters via mode selection and reference to ESS power, which is the result of ANN integration.

Suggested Citation

  • Tae-Gyu Kim & Hoon Lee & Chang-Gyun An & Junsin Yi & Chung-Yuen Won, 2023. "Hybrid AC/DC Microgrid Energy Management Strategy Based on Two-Step ANN," Energies, MDPI, vol. 16(4), pages 1-23, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1787-:d:1065133
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1787/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1787/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mostafa Kermani & Domenico Luca Carnì & Sara Rotondo & Aurelio Paolillo & Francesco Manzo & Luigi Martirano, 2020. "A Nearly Zero-Energy Microgrid Testbed Laboratory: Centralized Control Strategy Based on SCADA System," Energies, MDPI, vol. 13(8), pages 1-15, April.
    2. Sadaqat Ali & Zhixue Zheng & Michel Aillerie & Jean-Paul Sawicki & Marie-Cécile Péra & Daniel Hissel, 2021. "A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications," Energies, MDPI, vol. 14(14), pages 1-26, July.
    3. Maysam Abbasi & Ehsan Abbasi & Li Li & Ricardo P. Aguilera & Dylan Lu & Fei Wang, 2023. "Review on the Microgrid Concept, Structures, Components, Communication Systems, and Control Methods," Energies, MDPI, vol. 16(1), pages 1-36, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.
    2. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    3. Sulman Shahzad & Muhammad Abbas Abbasi & Hassan Ali & Muhammad Iqbal & Rania Munir & Heybet Kilic, 2023. "Possibilities, Challenges, and Future Opportunities of Microgrids: A Review," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    4. Fathy, Ahmed & Ferahtia, Seydali & Rezk, Hegazy & Yousri, Dalia & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid," Energy, Elsevier, vol. 247(C).
    5. Sameh Mahjoub & Larbi Chrifi-Alaoui & Saïd Drid & Nabil Derbel, 2023. "Control and Implementation of an Energy Management Strategy for a PV–Wind–Battery Microgrid Based on an Intelligent Prediction Algorithm of Energy Production," Energies, MDPI, vol. 16(4), pages 1-26, February.
    6. Paolo Tenti & Tommaso Caldognetto, 2023. "Integration of Local and Central Control Empowers Cooperation among Prosumers and Distributors towards Safe, Efficient, and Cost-Effective Operation of Microgrids," Energies, MDPI, vol. 16(5), pages 1-23, February.
    7. Hoon Lee & Jin-Wook Kang & Bong-Yeon Choi & Kyung-Min Kang & Mi-Na Kim & Chang-Gyun An & Junsin Yi & Chung-Yuen Won, 2021. "Energy Management System of DC Microgrid in Grid-Connected and Stand-Alone Modes: Control, Operation and Experimental Validation," Energies, MDPI, vol. 14(3), pages 1-26, January.
    8. Shanmugarajah Vinothine & Lidula N. Widanagama Arachchige & Athula D. Rajapakse & Roshani Kaluthanthrige, 2022. "Microgrid Energy Management and Methods for Managing Forecast Uncertainties," Energies, MDPI, vol. 15(22), pages 1-22, November.
    9. Teresa Pakulska, 2023. "The Energy Crisis—Looking at the Renewable Transition," Energies, MDPI, vol. 16(15), pages 1-3, July.
    10. Lilia Tightiz & Joon Yoo, 2022. "A Review on a Data-Driven Microgrid Management System Integrating an Active Distribution Network: Challenges, Issues, and New Trends," Energies, MDPI, vol. 15(22), pages 1-24, November.
    11. Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
    12. Md Shafiullah & Akib Mostabe Refat & Md Ershadul Haque & Dewan Mabrur Hasan Chowdhury & Md Sanower Hossain & Abdullah G. Alharbi & Md Shafiul Alam & Amjad Ali & Shorab Hossain, 2022. "Review of Recent Developments in Microgrid Energy Management Strategies," Sustainability, MDPI, vol. 14(22), pages 1-30, November.
    13. Timothé Gronier & William Maréchal & Christophe Geissler & Stéphane Gibout, 2022. "Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control," Energies, MDPI, vol. 16(1), pages 1-17, December.
    14. Abdellatif Elmouatamid & Radouane Ouladsine & Mohamed Bakhouya & Najib El Kamoun & Mohammed Khaidar & Khalid Zine-Dine, 2020. "Review of Control and Energy Management Approaches in Micro-Grid Systems," Energies, MDPI, vol. 14(1), pages 1-30, December.
    15. M. Bilal Nasir & Asif Hussain & Kamran Ali Khan Niazi & Mashood Nasir, 2022. "An Optimal Energy Management System (EMS) for Residential and Industrial Microgrids," Energies, MDPI, vol. 15(17), pages 1-18, August.
    16. Lu Liu & Yun Zeng, 2023. "Intelligent ISSA-Based Non-Singular Terminal Sliding-Mode Control of DC–DC Boost Converter Feeding a Constant Power Load System," Energies, MDPI, vol. 16(13), pages 1-23, June.
    17. Jonas Sievers & Thomas Blank, 2023. "A Systematic Literature Review on Data-Driven Residential and Industrial Energy Management Systems," Energies, MDPI, vol. 16(4), pages 1-21, February.
    18. Mahmoud F. Elmorshedy & Umashankar Subramaniam & Jagabar Sathik Mohamed Ali & Dhafer Almakhles, 2023. "Energy Management of Hybrid DC Microgrid with Different Levels of DC Bus Voltage for Various Load Types," Energies, MDPI, vol. 16(14), pages 1-32, July.
    19. Mostafa Kermani & Erfan Shirdare & Saram Abbasi & Giuseppe Parise & Luigi Martirano, 2021. "Elevator Regenerative Energy Applications with Ultracapacitor and Battery Energy Storage Systems in Complex Buildings," Energies, MDPI, vol. 14(11), pages 1-16, June.
    20. Sathesh Murugan & Mohana Jaishankar & Kamaraj Premkumar, 2022. "Hybrid DC–AC Microgrid Energy Management System Using an Artificial Gorilla Troops Optimizer Optimized Neural Network," Energies, MDPI, vol. 15(21), pages 1-19, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1787-:d:1065133. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.